Designing government subsidy schemes to promote the electric vehicle industry: A system dynamics model perspective

To ensure green and sustainable development, how to design effective subsidy schemes to promote the electric vehicle (EV) industry has become a critical problem faced by governments. In this paper, using a system dynamics (SD) model that incorporates the dynamic interactions between government, manufacturers, and consumers, we investigate the effects of different subsidy schemes (an acquisition subsidy vs a Research and Development (R&D) subsidy, as well as dynamic vs static subsidies) on the EV industry and environmental protection. Using empirical evidence from China, we verify the proposed model and predict that both an acquisition subsidy and an R&D subsidy can boost EV demand and reduce CO2 emissions. The acquisition subsidy helps to stimulate the sales of EVs more quickly and to a greater extent in the short term, but at great expense; for a given level of government expenditure, the R&D subsidy is more effective in promoting EV penetration and mitigating CO2 emissions. Moreover, the dynamic R&D subsidy scheme outperforms the static one in terms of subsidy efficiency. The study has implications for policy makers designing a subsidy scheme to promote the development of the EV industry.

Automated summary

In order to achieve green and sustainable development, the design of effective subsidy schemes to promote the electric vehicle (EV) industry is a critical concern for governments. This study uses a system dynamics model to investigate the effects of different subsidy schemes (acquisition subsidy vs R&D subsidy, dynamic vs static subsidies) on the EV industry and environmental protection. Empirical evidence from China confirms that both acquisition and R&D subsidies can boost EV demand and reduce CO2 emissions. However, the acquisition subsidy is more effective in the short term but comes at a higher cost, while the R&D subsidy is more effective in promoting EV penetration and mitigating CO2 emissions for a given level of government expenditure. Additionally, the dynamic R&D subsidy scheme outperforms the static one in terms of subsidy efficiency. These findings have implications for policymakers designing EV subsidy schemes.